The use of radiation to treat medical conditions comprises a known area of prior art endeavor. For example, radiation therapy comprises an important component of many treatment plans for reducing or eliminating unwanted tumors. Unfortunately, applied radiation does not inherently discriminate between unwanted areas and adjacent healthy tissues, organs, or the like that are desired or even critical to continued survival of the patient. As a result, radiation is ordinarily applied in a carefully administered manner pursuant to a radiation treatment plan to at least attempt to restrict the radiation to a given target volume.
Many radiation treatment plans provide for exposing the target volume to radiation from a number of different directions. Arc therapy, for example, comprises one such approach. In such a case it often becomes useful or necessary to also adjust various mechanical components (such as, for example, multi-leaf collimators) of the treatment system when moving the radiation source with respect to the target volume. A radiation treatment plan therefore often provides information regarding useful or necessary adjustments to various mechanical components of the treatment system during such a treatment.
A radiation treatment plan typically comprises specified values for each of a variety of treatment-platform parameters during each of a plurality of sequential fields. Radiation treatment plans for radiation treatment sessions are often generated through a so-called optimization process. As used herein, “optimization” will be understood to refer to improving a candidate treatment plan without necessarily ensuring that the optimized result is, in fact, the singular best solution. Such optimization often includes automatically adjusting (sometimes referred to as incrementing) one or more treatment parameters (often while observing one or more corresponding limits in these regards) and mathematically calculating a likely corresponding treatment result to identify a given set of treatment parameters that represent a good compromise between the desired therapeutic result and avoidance of undesired collateral effects.
Many prior art approaches employ multi-criteria optimization to develop a clinically worthy radiation treatment plan. The use of multi-criteria optimization, in turn, often involves use and investigation of a corresponding Pareto surface to identify and consider candidate radiation treatment plans. Unfortunately, a typical Pareto surface in such an application setting is relatively large as compared to the useful set of solutions. As a result, it can be very time consuming and/or consumptive of computational power to locate possibly useful plans using such an approach.
Elements in the figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. For example, the dimensions and/or relative positioning of some of the elements in the figures may be exaggerated relative to other elements to help to improve understanding of various embodiments of the present teachings. Also, common but well-understood elements that are useful or necessary in a commercially feasible embodiment are often not depicted in order to facilitate a less obstructed view of these various embodiments of the present teachings. Certain actions and/or steps may be described or depicted in a particular order of occurrence while those skilled in the art will understand that such specificity with respect to sequence is not actually required. The terms and expressions used herein have the ordinary technical meaning as is accorded to such terms and expressions by persons skilled in the technical field as set forth above except where different specific meanings have otherwise been set forth herein.